Social media. A rich source of insight and opportunity for companies. Why, it’s an article of faith that customers are talking…on their terms…where they want. So get out there and learn from them! See what this IBM executive says:

Companies that embrace social media as a source of insight will be rewarded. They’ll develop a deeper understanding of customer needs and will be able to attract new customers more easily. They’ll have a better shot at providing the products and services that the market wants – before the competition does.

It’s true, there are opportunities. But really, my sense is the opportunities lie on the marketing (read: sell) side of the house. Now social media occupies a large landscape. So how about narrowing focus, to Twitter. How useful are people’s tweets for customer insight? Specifically, giving companies a better handle on customers’ jobs-to-be-done?

tl;dr answer: Not so much. Lots of grousing about personal circumstances, and some silliness. But not much insight.

Saving and paying for college, in 450 tweets

Source: Mark J. Perry

To examine this question, I assumed the perspective of a financial firm trying to get a better handle on the “paying for college” jobs-to-be-done. In aspirational, emotional terms, college continues to be a top goal of parents for their children, and of teenagers as well. In economic terms, colleges have an insatiable appetite for tuition increases.

Importance for our children, increasing costs, need to save. Surely, there are some unfulfilled jobs-to-be-done out there. So I turned to Twitter to see what people were talking about. What needs were they expressing? What insight on this topic?

To see what people are saying, I ran Twitter searches on three terms:

college savings

“saving for college”

“pay for college”

I collected 150 tweets each for those three Twitter search terms (you can see them in this Google spreadsheet). With that data, I looked at (i) how many contained usable insight, (ii) what were the common words, and (iii) the collective sentiment.

Now, my research here is one of…oh say…a quadrillion possible customer insight areas to explore. Conclusions I draw here are not necessarily applicable to all areas. But it’s a good start.

Mining for jobs-to-be-done

Imagine you work for a large financial services company. You know in the U.S., people have put nearly $150 billion into 529 college savings plans. It’s a potent cocktail: lots of money; aspirations for, and symbolism of, a college degree; and escalating tuition. There have got to be opportunities to improve people’s lives here!

You want jobs-to-be-done, defined as people’s expressions of things they’re trying to get done in relation to saving and paying for college. Just what are they tweeting about out there?

You collect the tweets, and then categorize each tweet according to its value in understanding jobs-to-be-done:

No value

Points toward a job-to-be-done (a shadow of a job)

Direct expression of a job-to-be-done

In reviewing 450 separate tweets, here are the results:

Twitter search term

No value

Points to a JTBD

Direct JTBD

college savings

137

12

1

“saving for college”

141

9

0

“pay for college”

150

0

0

Totals

428

21

1

Looking at those, you begin to understand the challenge of looking at tweets as sources of customer insight.

Tweets with no value

By far, the most prevalent case was that the tweets provide no value in understanding what jobs people are trying to get done. At least, no actionable value. Below are examples of these types of tweets:

Many tweets in the “no value” category were of this type. Honest, authentic? You bet. Fuel for developing new innovations in products and services? Not so much. I’ll admit that value may be in the eye of the beholder. Perhaps someone wants to target scholarship-winning kids to buy new cars. But for the financial services firm, looking for insight from customers, these tweets don’t help.

Note that many of the tweets in this category weren’t from real people. They were marketing tweets by institutions. Which makes it hard to just dig in to those tweets. First you need to separate the manufactured marketing tweets from the honest expressions of individuals. Welcome to the jungle.

Tweets pointing to a job-to-be-done

I’ll admit, this categorization sounds funny: “pointing toward” a job. What does that mean? Look at a couple examples:

The tweets are not themselves the jobs-to-be-done. But they reflect jobs, if you read them carefully. In the first tweet, Raeleen wants to contribute to the college fund of her nephew. The larger story is that family, beyond the kid’s parents, can be part of the college savings effort. Here’s a definition of the job-to-be-done:

Situation: When I am planning my child’s college savings…Job: I want participation from family members and friends.Success means: Increased savings from a broad cross-section of family and friends.

The job reflected in the second tweet is one of structurally managing the college savings apart from other savings and cash expenditures.

There weren’t a lot of these, and many of them were pretty obvious jobs-to-be-done. But in hunting for the elusive job-to-be-done in the wild, their gamey, tough meat was better than nothing.

Direct expressions of jobs-to-be-done

After going through 450 tweets, I was sure I’d find at least one person tweeting a job-to-be-done. Maybe dazed by collecting and analyzing that many, I settled on the one below:

I see here an emotional job-to-be-done. Namely, the feeling of accomplishment that one feels in preparing financially for college. That’s a feeling that should be built on. I can tell you, when my wife and I put money into our kids’ 529 plans, we get that sense of accomplishment. Something that a financial institution should plug into more strongly.

So that was a nice job-to-be-done. However, as I said, slim pickings in finding jobs-to-be-done in tweets. Which should make you question how much of the presumed insight waiting to be gathered out there is actually…there.

But I did run the tweets through a couple other analyses to see what they turn up.

Sentiment analysis

For all these tweets about saving and paying for college, how was the sentiment? Does the mood tell us something about the jobs-to-be-done? Or at least provide some form of insight?

I ran them through a couple different tools: Sentiment Analyzer and Sentiment140. Sentiment Analyzer analyzed the 450 tweets I had collected. Sentiment140 ran an analysis on the most recent 19-25 tweets it could find related to a search term. While the bases of tweets differed, the two engines came up with remarkably similar results. Sentiment140 is on top, Sentiment Analyzer is on the bottom of the graphic below:

See how the college savings tweets are strongly positive. The general idea of college savings is a positive one, as college is a very strong emotional element for us. We may have attended ourselves, with memories from that period, and we want our kids to go. Then see how the mood swings to a darker one when tweets contain the phrase “pay for college”. It’s as if the more ‘transactional’ the experience becomes, the more negative the mood gets. Another difference is that tweets about “pay for college” overwhelmingly were by teenagers and young adults, expressing frustration related to affording college.

For marketing purposes at least, this sentiment analysis may have value in targeting people in different stages of the college saving spectrum.

Word trends

Another area explored is the commonality of words in the tweets used. Do they reveal latent jobs-to-be-done? I ran the tweets through Wordle:

The Wordles do reveal some interesting patterns. When people tweet about college savings, the most common words are plan, account, day, get. In this case, day is driven by the timing of when I collected the tweets. May 29th was upcoming, and it was U.S. national 529 Day (get it? 5/29). The most frequent word plan certainly makes sense, and in some ways fits the positive sentiment seen earlier. Thinking ahead about what’s needed to pay for college.

Notice the most frequent terms switch to start, money, need, parents in the “saving for college” Wordle. Let’s focus on the transition from plan seen in the college savings Wordle to start in the “saving for college” Wordle. It’s a transition from a more abstract concept to a task that one must undertake. The vibe switches to a get-things-done mentality.

Finally, note what dominates the “pay for college” Wordle: money, gonna, help, stripper. You might look at that and say, “stripper”? First, note that I converted the various stems of strip in the tweets to a single word, stripper, so as to better capture what showed up in a lot of the tweets. Essentially, a number of people (female and male) joking about becoming strippers to pay for school. I read these tweets as reflecting the steep costs of college, and teenagers/young adults not feeling like they have options to pay for it. A reflection of escalating tuition and cases where college savings were not available.

Usable insight on customer needs?

The title of this post highlights a particular aspect of insight that interests me: customer needs. On that score, I don’t find the tweets to be that valuable. As someone who is outside the financial services industry, I do find them to be gauges of what’s going on out there. An industry insider might already have a handle on what I discovered.

Here’s what makes tweets challenging to use for insight on customer needs:

Wide range to subjects: tweets run the gamut, even for a specific search term, and their volume makes it tough to sift through to find areas you want to explore

Odds are low that they’re speaking about core things they are looking to get done

People tweeting are not part of the market you’re seeking: for example, although there is $150 billion saved in U.S. 529 plans, these parents weren’t tweeting about saving and paying for college

Tweets have a one-off quality: follow-up and discussion to get deeper insights doesn’t happen

That’s my take. What do you think? Wouldn’t surprise me if others are seeing more value than I am. If you’re interested, you can check out the tweets I used for analysis on this Google spreadsheet.